Empirical evaluation of attention and task management as cognitive non-technical skills expertise of scrub nurses during realtime surgery

• Main Author: Koh, Ranieri Yung Ing.
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Theses and Dissertations
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Systems engineering
• Online Access: http://hdl.handle.net/10356/52429
• Institution: Nanyang Technological University

This dissertation aims to explore the fundamentals of cognitive non-technical skills of scrub nurses in particular, and proposes an integrated framework of cognitive non-technical skills, which covers the underlying aspects of cognitive non-technical skills and approaches to measure and validate the construct. Literature has identified non-technical skills, in particular, cognitive failures, as the direct determinants leading to accidents in the operating theatre, but no formal study has been done to investigate the cognitive factors directly influenced by expertise and influencing the performance of the scrub nurses. A cognitive non-technical skills framework guided by the theories of situation awareness is first drawn up, to define the cognitive factors influenced by expertise and in turn influencing performance. The proposed model consists of a main and a secondary framework. The main framework consists of four main aspects, namely situation awareness, task management, workload management and attention management. The three levels of situation awareness are the drivers behind the management of attention (level 1), reactive task management (level 2) and pro-active task management (level 3). The execution of all three levels in turn serves to maintain manageable levels of workload. This study adopted the use of eye-tracking to study the visual attention allocation and task management of 20 scrub nurses during standard real-life caesarean section surgeries, with 10 experienced nurses and 10 novice nurses. The data collection was done in a tertiary hospital in Singapore within a purely naturalistic setting. The participating nurses wore the eye-tracking device throughout the surgeries. Visual attention management and task management skills were analysed and evaluated based on the collected eye movement data. The results were in a direction that suggested that experienced nurses performed better than the novice nurses in most aspects. Experienced nurses were found to allocate significantly more attention to areas of high importance and areas related monitoring tasks. More importantly, the experienced nurses adhered more closely to the optimal expected value model of scanning (SEEV) than the novice nurses, with the difference highlighted in the stages of highest workload. In task management, experienced nurses showed greater resistance to interruptions during their tasks, especially to non-surgeon triggered interruptions during their surgical counts. They also displayed better anticipation in aiding the surgeon, taking shorter times to handover the instruments and making lesser mistakes. In a separate evaluation session by two subject matter experts, the experienced nurses were rated significantly higher in their cognitive non-technical skills than the novice nurses, further confirming better performance. In addition, correlation analyses found significant correlations within and between the attention management and task management indices. Better scanners were found to be better anticipators. They also had a tendency to allocate more attention to the areas of highest importance, also making lesser mistakes and being more resistant to interruptions. The findings from this study provide empirical evidence to 1) support the CONTS framework of cognitive non-technical skills of scrub nurses, 2) the existence of attention management and task management skills as cognitive non-technical skills of scrub nurses attributing to more ideal/optimal performance and 3) the existence of explicit relationships between the two that can help to guide training of cognitive non-technical skills to improve performance. The results also offer more confidence in drawing inferences regarding good and poor cognitive non-technical skills through expert and novice behaviours, generating deeper insights regarding the prediction, assessment and training of different aspects of cognitive non-technical skills, an area that research in healthcare has failed to address.